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coxrobust: Fit Robustly Proportional Hazards Regression Model

An implementation of robust estimation in Cox model. Functionality includes fitting efficiently and robustly Cox proportional hazards regression model in its basic form, where explanatory variables are time independent with one event per subject. Method is based on a smooth modification of the partial likelihood.

Version: 1.0.1
Depends: R (≥ 2.0.0)
Imports: survival
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 3.0.0), knitr
Published: 2022-04-06
DOI: 10.32614/CRAN.package.coxrobust
Author: Tadeusz Bednarski [aut], Filip Borowicz [aut], Shana Scogin ORCID iD [cre]
Maintainer: Shana Scogin <shanarscogin at gmail.com>
BugReports: https://github.com/ShanaScogin/coxrobust/issues
License: GPL-3
URL: https://github.com/ShanaScogin/coxrobust
NeedsCompilation: yes
Materials: NEWS
In views: Robust, Survival
CRAN checks: coxrobust results

Documentation:

Reference manual: coxrobust.pdf

Downloads:

Package source: coxrobust_1.0.1.tar.gz
Windows binaries: r-devel: coxrobust_1.0.1.zip, r-release: coxrobust_1.0.1.zip, r-oldrel: coxrobust_1.0.1.zip
macOS binaries: r-release (arm64): coxrobust_1.0.1.tgz, r-oldrel (arm64): coxrobust_1.0.1.tgz, r-release (x86_64): coxrobust_1.0.1.tgz, r-oldrel (x86_64): coxrobust_1.0.1.tgz
Old sources: coxrobust archive

Reverse dependencies:

Reverse imports: modeLLtest, MOSClip

Linking:

Please use the canonical form https://CRAN.R-project.org/package=coxrobust to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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